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DATEXIS
/
sproto

Text Classification
Transformers
Safetensors
English
sproto
multi-label-classification
long-tail-learning
medical
clinical-nlp
interpretability
prototypical-networks
ehr
custom_code
Model card Files Files and versions
xet
Community

Instructions to use DATEXIS/sproto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use DATEXIS/sproto with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="DATEXIS/sproto", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("DATEXIS/sproto", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
sproto
457 MB
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  • 2 contributors
History: 9 commits
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RamezCh
Update ReadME
5c17e82 verified 3 months ago
  • .gitattributes
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  • LICENSE
    4.57 kB
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  • README.md
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  • config.json
    1.05 kB
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  • configuration_sproto.py
    2.08 kB
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  • model.safetensors
    456 MB
    xet
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  • modeling_sproto.py
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  • output_example.png
    138 kB
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  • overview.png
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  • special_tokens_map.json
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  • tokenizer.json
    706 kB
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  • tokenizer_config.json
    488 Bytes
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